---
title: "Bangla MEG SaVANT Analysis"
author: "Swarnendu Moitra"
format:
html:
toc: true
code-fold: true
code-tools: true
embed-resources: true
execute:
echo: true
error: false
warning: false
cache: true
---
```{r}
path <- getwd ()
level_order <- c ('Gramm' , 'CatViol' , 'SemViol' )
```
# Load Libraries
```{r}
library (lme4)
library (tidyverse)
library (glmm)
library (ggplot2)
library (afex)
library (trimr)
require (car)
require (lattice)
require (itsadug)
library (ggpubr)
library (languageR)
library (plotrix)
library (Hmisc)
library (rlist)
library (effects)
library (sjPlot)
library (effectsize)
library (trimr)
library (jtools)
library (plotrix)
library (ggpubr)
library (gridExtra)
library (grid)
library (ggthemes)
source ('data/Themes.R' )
```
# Behavioural
## Online
# MEG
## Tark Localiser
6 conditions in this experiment, with 50 trials each. These conditions vary in length and Gaussian noise level as a visual mask. The trials were either 1-element or 4-element items. The 1-element items included 4 unique one-symbol items presented at the lowest Gaussian noise level (level 1), and 26 unique one-letter items presented at both the lowest (level 1) and highest Gaussian noise level (level 24). The one-symbol items were a triangle, a square, a diamond, or a circle **each containing a bar-diacritic over the element** and the one-letter items consisted single Bangla consonants. The 4-element items were 4-symbol strings presented only at the lowest Gaussian level (level 1) and 50 4-letter monomorphemic Bangla words presented at both noise level 1 and level 24. The four symbols used were again triangle, square, diamond, and circle, and were presented in four different permutations, joined together by a bar. Taking together we had a total of 300 trials in this experiment.
Dummy coded design matrix (2x4)
**Noise level** coded as 1:0 & 24:1
**Stimulus Type** coded as letter:0, word:1, symbol:2, string of symbols:3
## TYPE I (Working on it)
## TYPE II Tark Localiser (130 - 210)ms - Bilateral occipital and temporal regions
Analysis below is follwing Gwillams et al 2016
```{r}
tmin = 130
tmax = 210
# letter clean & lettersymbol :: RH, 150 - 189, p = 0.0164
ls_min = 145
ls_max = 189
p_ls = 0.0164
file_ls = "data/Tark/letter_symbol/TC_letter-nonLetter_bilateral occipital and temporal regions_0.14500000000000002-0.189_rh_p0.0164.csv"
# word clean & word symbols :: RH, 157 - 198 , p = 0.0196
ws_min_rh = 157
ws_max_rh = 198
p_ws_rh = 0.0196
file_ws_rh = "data/Tark/word_symbols/TC_letterWord-nonLetterWord_bilateral occipital and temporal regions_0.157-0.198_rh_p0.0196.csv"
# word clean & word symbols :: LH, 163 - 197 , p = 0.0173
ws_min_lh = 163
ws_max_lh = 197
p_ws_lh = 0.0173
file_ws_lh = "data/Tark/word_symbols/TC_letterWord-nonLetterWord_bilateral occipital and temporal regions_0.163-0.197_lh_p0.0173.csv"
```
#### letter vs symbol\| RH cluster (145 - 189)ms \| p = 0.0164
```{r}
data <- read_csv (file_ls, col_names = c ("Time" , "Participant" , "Item.no" , "cond" , "type" ,"hemi" , "dSPM" ))
data$ Condition <- paste ((data$ cond),(data$ type))
data$ Time <- data$ Time* 1000
#unique(data$Condition)
letterVsymbol <- data %>% filter (Participant != "B0025" ) %>% filter ((cond == "letter" & type == "clean" ) | (cond == "letter" & type == "symbol" ) )
letterVsymbol$ Condition[letterVsymbol$ Condition == "letter clean" ] <- "Letter"
letterVsymbol$ Condition[letterVsymbol$ Condition == "letter symbol" ] <- "Symbol"
letterVsymbol <- letterVsymbol %>%
dplyr:: group_by (
Time,
Condition,
hemi
) %>%
dplyr:: summarise (
SE = std.error (dSPM),
dSPM = mean (dSPM)
)
letterVsymbol <- letterVsymbol %>% filter (hemi == "dSPM-lh.stc" )
letterVsymbol_Bar <- letterVsymbol %>% filter (Time>= ls_min & Time <= ls_max) %>% dplyr:: group_by (Condition) %>% dplyr:: summarise (SE = std.error (dSPM), dSPM = mean (dSPM))
letterVsymbol_Bar <- letterVsymbol_Bar %>% mutate (Condition = as.factor (Condition))
letterVsymbol_Bar$ Condition <- relevel (letterVsymbol_Bar$ Condition, ref = "Letter" )
```
 {fig-align="center"}
```{r}
#| label: fig-letter_symbol_rh
letterVsymbol_timeseries <- ggplot (letterVsymbol, aes (x = Time, y = dSPM, col = Condition, linetype = Condition)) +
geom_line (aes (group = paste (Condition)),size = 1 ) +
#annotate('rect',xmin=tmin, xmax=tmax, alpha=0.12,ymin=-Inf,ymax=Inf,fill="darkgrey") +
annotate ('text' ,x= (ls_min + ls_max)/ 2 , y= 0.7 , label = "*" , size = 20 ) +
annotate ('rect' ,xmin= ls_min, xmax= ls_max, alpha= 0.2 ,ymin= - Inf ,ymax= Inf ,fill= "darkgrey" ) +
# annotate('rect',xmin=tmin - 50, xmax=tmax + 50, alpha=0.1,ymin=-Inf,ymax=Inf,fill="green") +
# annotate('rect',xmin=-Inf, xmax=tmin, alpha=0.075,ymin=-Inf,ymax=Inf,fill="#000000") +
# annotate('rect',xmin=tmax, xmax=Inf, alpha=0.075,ymin=-Inf,ymax=Inf,fill="#666666") +
# scale_colour_manual("",values=c("#E63946","#276FBF", "#545083", "#FF8888", "#FF0000", "#FF8888")) +
scale_colour_manual ("" ,values= c ("deeppink" ,"dodgerblue" , "#545083" , "#FF8888" , "#FF0000" , "#FF8888" )) +
scale_linetype_manual ("" ,values= c ("solid" , "twodash" , "solid" , "dashed" , "solid" , "dashed" )) +
# scale_fill_manual("",values=c("#E63946","#545083", "#545083", "#FF8888", "#FF0000", "#FF8888")) +
geom_ribbon (aes (ymin = dSPM - SE, ymax = dSPM + SE, fill = Condition, group= Condition), alpha = 0.2 , col = NA , show.legend = FALSE ) +
scale_y_continuous ("Activation (dSPM)" ,expand= c (0 ,0 ), limits = c (- 1 , 1 )) + scale_x_continuous ("Time (ms)" , expand= c (0 ,0 ), limits = c (- 50 , 350 )) + theme (legend.position= "bottom" ) +
theme_minimal () + theme (panel.grid.major = element_blank (),
panel.grid.minor = element_blank (),
axis.title = element_text (size = 14 , face = "bold" ),
axis.text = element_text (size = 12 ), legend.position = "none" ) +
geom_hline (yintercept= 0 , linetype= "dotted" ) + geom_vline (xintercept= 0 , linetype= "dotted" )
letterVsymbol_bar <- ggplot (letterVsymbol_Bar, aes (x= Condition, y= dSPM,fill= Condition)) +
geom_bar (stat = "identity" , width = 0.7 , position = position_dodge (0.7 ), show.legend = FALSE , color= "#545083" )+
#scale_x_discrete(limits = Conditions) + facet_wrap( ~Prefix) +
ylab ("dSPM" ) +
xlab ("Conditions" ) +
scale_fill_manual ("" ,values= c ("deeppink" ,"dodgerblue" , "#545083" , "#FF8888" , "#FF0000" , "#FF8888" )) +
#theme_Publication()+
# coord_cartesian(ylim = c(0, 1150)) +
# scale_y_continuous(expand = expansion(mult = c(0, 0.05)))+
# geom_signif(
# comparisons = list(c("Grammatical", "Pseudowords")),
# margin_top = 0.8,
# step_increase = 0.09,
# tip_length = 0.5,
# annotation = c("***")
# )+
geom_hline (yintercept= 0 , linetype= "dotted" ) + geom_vline (xintercept= 0 , linetype= "dotted" ) +
theme_minimal () + theme (panel.grid.major = element_blank (),
panel.grid.minor = element_blank (),
axis.title = element_text (size = 14 , face = "bold" ),
axis.text = element_text (size = 12 )) +
#geom_errorbar function is used to plot error bars
geom_errorbar (aes (ymin= dSPM- SE,
ymax= dSPM+ SE,
width= 0.3 ))
Plots_bars <- grid.arrange (letterVsymbol_bar + theme_Publication_SwarMoi () ,(letterVsymbol_timeseries + theme_Publication_SwarMoi () + theme (legend.position = "none" )),nrow= 1 , widths= c (4 ,9 ));
```
```{r}
#| label: tbl-letterVsymbol-rh
knitr:: kable (letterVsymbol_Bar)
```
1. word vs. symbols (LH)
#### Cluster word vs. symbols: LH cluster (163 - 197)ms \| p = 0.0173
```{r}
data <- read_csv (file_ws_lh, col_names = c ("Time" , "Participant" , "Item.no" , "cond" , "type" ,"hemi" , "dSPM" ))
data$ Condition <- paste ((data$ cond),(data$ type))
data$ Time <- data$ Time* 1000
#unique(data$Condition)
wordVsymbols_lh <- data %>% filter (Participant != "B0025" ) %>% filter (((cond == "word" & type == "clean" ) | (cond == "word" & type == "symbols" ) ))
wordVsymbols_lh$ Condition[wordVsymbols_lh$ Condition == "word clean" ] <- "Word"
wordVsymbols_lh$ Condition[wordVsymbols_lh$ Condition == "word symbols" ] <- "Symbols"
wordVsymbols_lh <- wordVsymbols_lh %>%
dplyr:: group_by (
Time,
Condition,
hemi
) %>%
dplyr:: summarise (
SE = std.error (dSPM),
dSPM = mean (dSPM)
)
wordVsymbols_lh <- wordVsymbols_lh %>% filter (hemi == "dSPM-lh.stc" )
#wordVsymbols_lh$Condition = with(wordVsymbols_lh, reorder(Word, Symbols)
wordVsymbols_Bar_lh <- wordVsymbols_lh %>% filter (Time>= ws_min_lh & Time <= ws_max_lh) %>% dplyr:: group_by (Condition) %>% dplyr:: summarise (SE = std.error (dSPM), dSPM = mean (dSPM))
wordVsymbols_Bar_lh <- wordVsymbols_Bar_lh %>% mutate (Condition = as.factor (Condition))
wordVsymbols_Bar_lh$ Condition <- relevel (wordVsymbols_Bar_lh$ Condition, ref = "Word" )
```
 {fig-align="center"}
```{r}
wordVsymbols_timeseries_lh <- ggplot (wordVsymbols_lh, aes (x = Time, y = dSPM, col = Condition, linetype = Condition)) +
geom_line (aes (group = Condition),size = 1 ) +
#annotate('rect',xmin=tmin, xmax=tmax, alpha=0.12,ymin=-Inf,ymax=Inf,fill="darkgrey") +
annotate ('text' ,x= (ws_min_lh + ws_max_lh)/ 2 , y= 0.7 , label = "*" , size = 20 ) +
annotate ('rect' ,xmin= ws_min_lh, xmax= ws_max_lh, alpha= 0.2 ,ymin= - Inf ,ymax= Inf ,fill= "darkgrey" ) +
# annotate('rect',xmin=tmin - 50, xmax=tmax + 50, alpha=0.1,ymin=-Inf,ymax=Inf,fill="green") +
# annotate('rect',xmin=-Inf, xmax=tmin, alpha=0.075,ymin=-Inf,ymax=Inf,fill="#000000") +
# annotate('rect',xmin=tmax, xmax=Inf, alpha=0.075,ymin=-Inf,ymax=Inf,fill="#666666") +
# scale_colour_manual("",values=c("#E63946","#276FBF", "#545083", "#FF8888", "#FF0000", "#FF8888")) +
scale_colour_manual ("" ,values= c ("deeppink" ,"dodgerblue" , "#545083" , "#FF8888" , "#FF0000" , "#FF8888" )) +
scale_linetype_manual ("" ,values= c ("solid" , "twodash" , "solid" , "dashed" , "solid" , "dashed" )) +
# scale_fill_manual("",values=c("#E63946","#545083", "#545083", "#FF8888", "#FF0000", "#FF8888")) +
geom_ribbon (aes (ymin = dSPM - SE, ymax = dSPM + SE, fill = Condition, group= Condition), alpha = 0.2 , col = NA , show.legend = FALSE ) +
scale_y_continuous ("Activation (dSPM)" ,expand= c (0 ,0 ), limits = c (- 1 , 1 )) + scale_x_continuous ("Time (ms)" , expand= c (0 ,0 ), limits = c (- 50 , 350 )) + theme (legend.position= "bottom" ) +
theme_minimal () + theme (panel.grid.major = element_blank (),
panel.grid.minor = element_blank (),
axis.title = element_text (size = 14 , face = "bold" ),
axis.text = element_text (size = 12 ), legend.position = "none" ) +
geom_hline (yintercept= 0 , linetype= "dotted" ) + geom_vline (xintercept= 0 , linetype= "dotted" )
wordVsymbols_bar_lh <- ggplot (wordVsymbols_Bar_lh, aes (x= Condition, y= dSPM,fill= Condition)) +
geom_bar (stat = "identity" , width = 0.7 , position = position_dodge (0.7 ), show.legend = FALSE , color= "#545083" )+
#scale_x_discrete(limits = Conditions) + facet_wrap( ~Prefix) +
ylab ("dSPM" ) +
xlab ("Conditions" ) +
scale_fill_manual ("" ,values= c ("deeppink" ,"dodgerblue" , "#545083" , "#FF8888" , "#FF0000" , "#FF8888" )) +
#theme_Publication()+
# coord_cartesian(ylim = c(0, 1150)) +
# scale_y_continuous(expand = expansion(mult = c(0, 0.05)))+
# geom_signif(
# comparisons = list(c("Grammatical", "Pseudowords")),
# margin_top = 0.8,
# step_increase = 0.09,
# tip_length = 0.5,
# annotation = c("***")
# )+
geom_hline (yintercept= 0 , linetype= "dotted" ) + geom_vline (xintercept= 0 , linetype= "dotted" ) +
theme_minimal () + theme (panel.grid.major = element_blank (),
panel.grid.minor = element_blank (),
axis.title = element_text (size = 14 , face = "bold" ),
axis.text = element_text (size = 12 )) +
#geom_errorbar function is used to plot error bars
geom_errorbar (aes (ymin= dSPM- SE,
ymax= dSPM+ SE,
width= 0.3 ))
```
```{r}
#| label: fig-word_symbols_lh
Plot_wordSymbol_lh <- grid.arrange (wordVsymbols_bar_lh + theme_Publication_SwarMoi () ,(wordVsymbols_timeseries_lh + theme_Publication_SwarMoi () + theme (legend.position = "none" )),nrow= 1 , widths= c (4 ,9 ));
```
#### RH cluster : 157 - 198 ms \| p =0.0196
```{r}
data <- read_csv (file_ws_rh, col_names = c ("Time" , "Participant" , "Item.no" , "cond" , "type" ,"hemi" , "dSPM" ))
data$ Condition <- paste ((data$ cond),(data$ type))
data$ Time <- data$ Time* 1000
#unique(data$Condition)
wordVsymbols_rh <- data %>% filter (Participant != "B0025" ) %>% filter (((cond == "word" & type == "clean" ) | (cond == "word" & type == "symbols" ) ))
wordVsymbols_rh$ Condition[wordVsymbols_rh$ Condition == "word clean" ] <- "Word"
wordVsymbols_rh$ Condition[wordVsymbols_rh$ Condition == "word symbols" ] <- "Symbols"
wordVsymbols_rh <- wordVsymbols_rh %>%
dplyr:: group_by (
Time,
Condition,
hemi
) %>%
dplyr:: summarise (
SE = std.error (dSPM),
dSPM = mean (dSPM)
)
wordVsymbols_rh <- wordVsymbols_rh %>% filter (hemi == "dSPM-rh.stc" )
#wordVsymbols_lh$Condition = with(wordVsymbols_lh, reorder(Word, Symbols)
wordVsymbols_Bar_rh <- wordVsymbols_rh %>% filter (Time>= ws_min_rh & Time <= ws_max_rh) %>% dplyr:: group_by (Condition) %>% dplyr:: summarise (SE = std.error (dSPM), dSPM = mean (dSPM))
wordVsymbols_Bar_rh <- wordVsymbols_Bar_rh %>% mutate (Condition = as.factor (Condition))
wordVsymbols_Bar_rh$ Condition <- relevel (wordVsymbols_Bar_rh$ Condition, ref = "Word" )
```
```{r}
#| label: tbl-wordVsymbols_rh
knitr:: kable (wordVsymbols_Bar_rh)
```
```{r}
wordVsymbols_timeseries_rh <- ggplot (wordVsymbols_rh, aes (x = Time, y = dSPM, col = Condition, linetype = Condition)) +
geom_line (aes (group = Condition),size = 1 ) +
#annotate('rect',xmin=tmin, xmax=tmax, alpha=0.12,ymin=-Inf,ymax=Inf,fill="darkgrey") +
annotate ('text' ,x= (ws_min_rh + ws_max_rh)/ 2 , y= 0.7 , label = "*" , size = 20 ) +
annotate ('rect' ,xmin= ws_min_rh, xmax= ws_max_rh, alpha= 0.2 ,ymin= - Inf ,ymax= Inf ,fill= "darkgrey" ) +
# annotate('rect',xmin=tmin - 50, xmax=tmax + 50, alpha=0.1,ymin=-Inf,ymax=Inf,fill="green") +
# annotate('rect',xmin=-Inf, xmax=tmin, alpha=0.075,ymin=-Inf,ymax=Inf,fill="#000000") +
# annotate('rect',xmin=tmax, xmax=Inf, alpha=0.075,ymin=-Inf,ymax=Inf,fill="#666666") +
# scale_colour_manual("",values=c("#E63946","#276FBF", "#545083", "#FF8888", "#FF0000", "#FF8888")) +
scale_colour_manual ("" ,values= c ("deeppink" ,"dodgerblue" , "#545083" , "#FF8888" , "#FF0000" , "#FF8888" )) +
scale_linetype_manual ("" ,values= c ("solid" , "twodash" , "solid" , "dashed" , "solid" , "dashed" )) +
# scale_fill_manual("",values=c("#E63946","#545083", "#545083", "#FF8888", "#FF0000", "#FF8888")) +
geom_ribbon (aes (ymin = dSPM - SE, ymax = dSPM + SE, fill = Condition, group= Condition), alpha = 0.2 , col = NA , show.legend = FALSE ) +
scale_y_continuous ("Activation (dSPM)" ,expand= c (0 ,0 ), limits = c (- 1 , 1 )) + scale_x_continuous ("Time (ms)" , expand= c (0 ,0 ), limits = c (- 50 , 350 )) + theme (legend.position= "bottom" ) +
theme_minimal () + theme (panel.grid.major = element_blank (),
panel.grid.minor = element_blank (),
axis.title = element_text (size = 14 , face = "bold" ),
axis.text = element_text (size = 12 ), legend.position = "none" ) +
geom_hline (yintercept= 0 , linetype= "dotted" ) + geom_vline (xintercept= 0 , linetype= "dotted" )
wordVsymbols_bar_rh <- ggplot (wordVsymbols_Bar_rh, aes (x= Condition, y= dSPM,fill= Condition)) +
geom_bar (stat = "identity" , width = 0.7 , position = position_dodge (0.7 ), show.legend = FALSE , color= "#545083" )+
#scale_x_discrete(limits = Conditions) + facet_wrap( ~Prefix) +
ylab ("dSPM" ) +
xlab ("Conditions" ) +
scale_fill_manual ("" ,values= c ("deeppink" ,"dodgerblue" , "#545083" , "#FF8888" , "#FF0000" , "#FF8888" )) +
#theme_Publication()+
# coord_cartesian(ylim = c(0, 1150)) +
# scale_y_continuous(expand = expansion(mult = c(0, 0.05)))+
# geom_signif(
# comparisons = list(c("Grammatical", "Pseudowords")),
# margin_top = 0.8,
# step_increase = 0.09,
# tip_length = 0.5,
# annotation = c("***")
# )+
geom_hline (yintercept= 0 , linetype= "dotted" ) + geom_vline (xintercept= 0 , linetype= "dotted" ) +
theme_minimal () + theme (panel.grid.major = element_blank (),
panel.grid.minor = element_blank (),
axis.title = element_text (size = 14 , face = "bold" ),
axis.text = element_text (size = 12 )) +
#geom_errorbar function is used to plot error bars
geom_errorbar (aes (ymin= dSPM- SE,
ymax= dSPM+ SE,
width= 0.3 ))
#wordVsymbols_timeseries_rh
#wordVsymbols_bar_rh
```

```{r}
#| label: fig-word_symbols_rh
Plot_wordSymbol_rh <- grid.arrange (wordVsymbols_bar_rh + theme_Publication_SwarMoi () ,(wordVsymbols_timeseries_lh + theme_Publication_SwarMoi () + theme (legend.position = "none" )),nrow= 1 , widths= c (4 ,9 ))
```
## Decomposition
### aROI - LMM
#### Cluster 1
```{r}
col_names = c ("Participant" , "Item.no" , "Prefix" , "hemi" , "wordFreq" , "stemFreq" , "ITEMNO" , "Condition" , "stim" ,"dSPM" )
aROI_Cluster_1_Tark <- read_csv ("data/M170/Tark_Cluster_1/aROI_Cluster_1_Tark.csv" , col_names = col_names)
GA_aROI_Cluster_1_Tark <- aROI_Cluster_1_Tark %>% filter (Condition != "SemViol" & Condition != "CatViol" ) %>% group_by (Condition) %>% dplyr:: summarise (GA_dSPM = mean (dSPM))
knitr:: kable (GA_aROI_Cluster_1_Tark)
```
#### Cluster 2
```{r}
# col_names = c("Participant", "Item.no", "Prefix", "hemi", "wordFreq", "stemFreq", "ITEMNO", "Condition", "stim","dSPM")
# aROI_Cluster_2_Tark <- read_csv("data/M170/Tark_Cluster_1/aROI_Cluster_2_Tark.csv", col_names = col_names)
#
# GA_aROI_Cluster_2_Tark <- aROI_Cluster_1_Tark %>% filter(Condition != "SemViol" & Condition != "CatViol") %>% group_by(Condition) %>% dplyr::summarise(GA_dSPM = mean(dSPM))
```
#### Cluster 3
### FROI
 {fig-align="center"}
```{r}
col_names = c ("Participant" , "Item.no" , "Prefix" , "hemi" , "wordFreq" , "stemFreq" , "ITEMNO" , "Condition" , "stim" ,"dSPM" )
M170_Tark_fROI <- read_csv ("data/M170/froi_TP_M170_Tark.csv" , col_names = col_names)
M170_Tark_fROI <- M170_Tark_fROI %>%
filter (hemi == "dSPM-lh.stc" ) %>%
filter (Condition != "SemViol" & Condition != "CatViol" ) %>%
select (- stim) %>%
mutate (log_stemFreq = log (stemFreq), log_wordFreq = log (wordFreq), TP = (wordFreq/ stemFreq), logTP = log (TP), logTP_div = (log_wordFreq/ log_stemFreq))
M170_Tark_fROI <- M170_Tark_fROI %>%
mutate (
Participant = as.factor (Participant),
dSPM = as.numeric (dSPM),
Condition = as.factor (Condition),
item = as.factor (ITEMNO)
)
#str(M170_Tark_fROI)
M170_Tark_fROI$ Prefix <- relevel (M170_Tark_fROI$ Condition, ref= "Gramm" )
M170_Tark_fROI_main <- lmer (dSPM ~ Condition * logTP_div + log_stemFreq + log_wordFreq + (1 | Participant) + (1 | ITEMNO), data = M170_Tark_fROI, REML = F)
tab_model (M170_Tark_fROI_main)
summary (M170_Tark_fROI_main)
```
```{r}
library (interactions)
interact_plot (M170_Tark_fROI_main, pred = "logTP_div" , modx = "Condition" , interval = TRUE , int.type = "confidence" , int.width = .8 , x.label = "Transition Probability" , y.label = "dSPM" , color.class = "Oranges" )
```
## Recomposition
```{r}
X <- tribble (
~ Prefix, ~ Condition, ~ PrefixType,
"CatViolDU" , "CatViol" , "DU" ,
"CatViolPROTI" , "CatViol" ,"PROTI" ,
"GrammDU" , "Gramm" ,"DU" ,
"GrammPROTI" , "Gramm" ,"PROTI" ,
"SemViolDU" , "SemViol" ,"DU" ,
"SemViolPROTI" , "SemViol" ,"PROTI" ,
"Filler" , "Filler" ,"Fill" ,
)
```
### TL: RH_TemporalLobe_244-286_p0.0197
 {fig-align="center"}
```{r}
RH_Temporal <- read_csv ("data/SAVANT/CatViol_RH_244-286_p0.0197.csv" , col_names = c ("Participant" , "Prefix" ,"hemi" , "dSPM" ))
RH_Temporal = RH_Temporal %>% left_join (X)
RH_Temporal <- RH_Temporal %>% select (! hemi) %>% group_by (Condition) %>% summarise (SE = std.error (dSPM),dSPM = mean (dSPM))
RH_Temporal_TC <- read_csv ("data/SAVANT/TC_CatViol_RH_244-286_p0.0197.csv" , col_names = c ("time" , "Participant" , "Prefix" ,"hemi" , "dSPM" ))
RH_Temporal_TC = RH_Temporal_TC %>% left_join (X)
RH_Temporal_TC$ time = RH_Temporal_TC$ time* 1000
RH_Temporal_TC <- RH_Temporal_TC %>% filter (between (time, 244 , 286 )) %>% group_by (Condition) %>% summarise (SE = std.error (dSPM),
dSPM = mean (dSPM))
RH_temporal_plot <- RH_Temporal %>% filter (Condition != "Filler" ) %>% ggplot (aes (x= factor (Condition, level = level_order),y= dSPM,fill= Condition)) +
# geom_bar function is used to plot bars of barplot
geom_bar (stat = "identity" , width = 0.95 , position = position_dodge (0.1 ), show.legend = FALSE )+
#scale_x_discrete(limits = Conditions) + facet_wrap( ~Prefix) +
ylab ("dSPM" ) +
xlab ("Conditions" ) +
scale_fill_manual (values = c ("blue" , "green" ,"red" ))+
geom_errorbar (aes (ymin= dSPM- SE,
ymax= dSPM+ SE,
width= 0.3 ))+
theme_minimal () +
theme (axis.text.x = element_text (size = 15 , angle = 0 , hjust = .5 , vjust = .5 , face = "plain" ),
axis.text.y = element_text (size = 15 , angle = 0 , hjust = 1 , vjust = 0 , face = "plain" ),
axis.title.x = element_text (size = 18 , angle = 0 , hjust = .5 , vjust = 0 , face = "plain" ),
axis.title.y = element_text (size = 18 , angle = 90 , hjust = .5 , vjust = .5 , face = "plain" ))
RH_temporal_plot
```
```{r}
#| label: tbl-TL_rh
knitr:: kable (RH_Temporal)
```
### OF : LH OF 424-452_p0.0472
 {fig-align="center"}
```{r}
LH_OF <- read_csv ("data/SAVANT/OF_LH_424-452_p0.0472.csv" , col_names = c ("Participant" , "Prefix" ,"hemi" , "dSPM" ))
LH_OF = LH_OF %>% left_join (X)
LH_OF <- LH_OF %>% select (! hemi) %>% group_by (Condition,Prefix, PrefixType) %>% summarise (SE = std.error (dSPM),
dSPM = mean (dSPM))
LH_OF_TC <- read_csv ("data/SAVANT/TC_OF_LH_424-452_p0.0472.csv" , col_names = c ("time" , "Participant" , "Prefix" ,"hemi" , "dSPM" ))
LH_OF_TC = LH_OF_TC %>% left_join (X)
LH_OF_TC$ time = LH_OF_TC$ time* 1000
LH_OF_TC <- LH_OF_TC %>% filter (between (time, 424 , 452 )) %>% group_by (Condition, Prefix, PrefixType) %>% summarise (SE = std.error (dSPM),
dSPM = mean (dSPM))
LH_OF_plot <- LH_OF %>% filter (Condition != "Filler" ) %>% ggplot (aes (x= factor (Condition, level = level_order),y= dSPM,fill= Condition)) +
# geom_bar function is used to plot bars of barplot
geom_bar (stat = "identity" , width = 0.99 , position = position_dodge (0.1 ), show.legend = FALSE )+
#scale_x_discrete(limits = Conditions) + facet_wrap( ~Prefix) +
ylab ("dSPM" ) +
xlab ("Conditions" ) +
facet_wrap (~ PrefixType) +
# scale_fill_manual(values = c("blue", "lightblue" , "green", "lightgreen" ,"red", "pink"))+
scale_fill_manual (values = c ("blue" , "green" ,"red" ))+
geom_errorbar (aes (ymin= dSPM- SE,
ymax= dSPM+ SE,
width= 0.3 ))+
theme_minimal () +
theme (axis.text.x = element_text (size = 18 , angle = 0 , hjust = .5 , vjust = .5 , face = "plain" ),
axis.text.y = element_text (size = 15 , angle = 0 , hjust = 1 , vjust = 0 , face = "plain" ),
axis.title.x = element_text (size = 18 , angle = 0 , hjust = .5 , vjust = 0 , face = "plain" ),
axis.title.y = element_text (size = 18 , angle = 90 , hjust = .5 , vjust = .5 , face = "plain" ))
LH_OF_plot
```
```{r}
#| label: tbl-OF_lh
knitr:: kable (LH_OF)
```
## Exploratory Analysis
### OF : LH_OF Early (238-279_p0.0049)
 {fig-align="center"}
```{r}
LH_OF_early <- read_csv ("data/SAVANT/CatViol_LH_earlyOF_238-279_p0.0049.csv" , col_names = c ("Participant" , "Prefix" ,"hemi" , "dSPM" ))
LH_OF_early = LH_OF_early %>% left_join (X)
LH_OF_early <- LH_OF_early %>% select (! hemi) %>% group_by (Condition) %>% summarise (SE = std.error (dSPM),
dSPM = mean (dSPM))
LH_OF_early_TC <- read_csv ("data/SAVANT/TC_CatViol_LH_earlyOF_238-279_p0.0049.csv" , col_names = c ("time" , "Participant" , "Prefix" ,"hemi" , "dSPM" ))
LH_OF_early_TC = LH_OF_early_TC %>% left_join (X)
LH_OF_early_TC$ time = LH_OF_early_TC$ time* 1000
LH_OF_early_TC <- LH_OF_early_TC %>% filter (between (time, 238 , 279 )) %>% group_by (Condition) %>% summarise (SE = std.error (dSPM),
dSPM = mean (dSPM))
LH_OF_early_plot <- LH_OF_early %>% filter (Condition != "Filler" ) %>% ggplot (aes (x= factor (Condition, level = level_order),y= dSPM,fill= Condition)) +
# geom_bar function is used to plot bars of barplot
geom_bar (stat = "identity" , width = 0.95 , position = position_dodge (0.1 ), show.legend = FALSE )+
#scale_x_discrete(limits = Conditions) + facet_wrap( ~Prefix) +
ylab ("dSPM" ) +
xlab ("Conditions" ) +
scale_fill_manual (values = c ("blue" , "green" ,"red" ))+
geom_errorbar (aes (ymin= dSPM- SE,
ymax= dSPM+ SE,
width= 0.3 ))+
theme_minimal () +
theme (axis.text.x = element_text (size = 15 , angle = 0 , hjust = .5 , vjust = .5 , face = "plain" ),
axis.text.y = element_text (size = 15 , angle = 0 , hjust = 1 , vjust = 0 , face = "plain" ),
axis.title.x = element_text (size = 18 , angle = 0 , hjust = .5 , vjust = 0 , face = "plain" ),
axis.title.y = element_text (size = 18 , angle = 90 , hjust = .5 , vjust = .5 , face = "plain" ))
LH_OF_early_plot
```
```{r}
#| label: tbl-OF_early_lh
knitr:: kable (LH_OF_early)
```